CSC 520 Artificial Intelligence I
 

Introduction and overview of artificial intelligence. Elements of AI problem-solving techniques. State spaces and search techniques, including heuristic search (hill-climbing and A*). Logic (first-order predicate calculus) and theorem proving (unification, resolution theorem proving). Advanced topics in machine learning, reasoning under uncertainty (Bayesian reasoning), and natural language processing as time permits. 3 credit hours.

 
   

• Prerequisite
 

Undergraduate degree in computer science with courses in data structures (CSC 316) AND applied discrete mathematics (CSC 226) or background in symbolic logic. Note: CSC 226 and 316 are offered as a part of the Computer Programming Certificate and can be taken online to fulfill this prerequisite.


• Course Objectives
 

CSC520 is the foundational artificial intelligence course. It is intended to prepare students for advanced courses in AI. A student successfully completing this course will be able to: (1) Identify representations and methodologies useful in the development of computer-based systems which exhibit aspects of intelligent behavior; (2) Program simple intelligent agents to operate in simple environments; (3) Identify the utility and limitations of knowledge representation methodologies such as propositional and predicate logic, rule-based systems, and probabilistic systems; (4) Identify the utility and limitations of companion reasoning methods, including resolution, rule processing, probabilistic reasoning, machine learning, and natural language processing; (5) Distinguish various uninformed and informed search algorithms and identify when each is appropriate; (6) Design and implement a series of simple intelligent agents of increasing complexity.


• Course Requirements
 

HOMEWORK: Programming Assignments (2-3), Other (1-2)

EXAMINATIONS: Midterm and Final Exam

SOFTWARE REQUIREMENTS: Programming assignments use Java

PROJECTS: N/A


• Textbook
 

Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd Edition , Prentice Hall, 2010, ISBN 978-0-13-604259.


• Computer and Internet Requirements
 

NCSU and Engineering Online have recommended minimum specifications for computers. For details, click here.


• Instructor
 

Dr. Dennis R. Bahler, Associate Professor
Computer Science-Engineering
Engineering Building II(Eb2), Box 8206
NCSU Campus
Raleigh, NC 27695

Phone: 919-515-3369
Fax: 919-515-7896
Email: bahler@ncsu.edu